Using Hyperspectral Analysis As a Potential High Throughput Phenotyping Tool in GWAS for Protein Content of Rice Quality

Overview

Journal Plant Methods

Publisher Biomed Central

Specialty Biology

Date 2019 May 30

PMID 31139243

Citations 21

Authors

Dawei Sun

Haiyan Cen

Haiyong Weng

Liang Wan

Alwaseela Abdalla

Ahmed Islam El-Manawy

Yueming Zhu

Nan Zhao

Haowei Fu

Juan Tang

Xiaolong Li

Hongkun Zheng

Qingyao Shu

Fei Liu

Yong He

Affiliations

Soon will be listed here.

Abstract

Background: The advances of hyperspectral technology provide a new analytic means to decrease the gap of phenomics and genomics caused by the fast development of plant genomics with the next generation sequencing technology. Through hyperspectral technology, it is possible to phenotype the biochemical attributes of rice seeds and use the data for GWAS.

Results: The results of correlation analysis indicated that Normalized Difference Spectral Index (NDSI) had high correlation with protein content (PC) with R = 0.68. Based on GWAS analysis using all the traits, NDSI was able to identify the same SNP loci as rice protein content that was measured by traditional methods. In total, hyperspectral trait NDSI identified all the 43 genes that were identified by biochemical trait PC. NDSI identified 1 extra SNP marker on chromosome 1, which annotated extra 22 genes that were not identified by PC. Kegg annotation results showed that traits NDSI annotated 3 pathways that are exactly the same as PC. The cysteine and methionine metabolic pathway identified by both NDSI and PC was reported important for biosynthesis and metabolism of some of amino acids/protein in rice seeds.

Conclusion: This study combined hyperspectral technology and GWAS analysis to dissect PC of rice seeds, which was high throughput and proven to be able to apply to GWAS as a new phenotyping tool. It provided a new means to phenotype one of the important biochemical traits for the determination of rice quality that could be used for genetic studies.

Citing Articles

Integrative phenomics, metabolomics and genomics analysis provides new insights for deciphering the genetic basis of metabolism in polished rice.

Feng H, Li Y, Dai G, Yang Z, Song J, Lu B Genome Biol. 2025; 26(1):55.

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Exploring the potential of microscopic hyperspectral, Raman, and LIBS for nondestructive quality assessment of diverse rice samples.

Guo J, Jiang S, Lu B, Zhang W, Zhang Y, Hu X Plant Methods. 2025; 21(1):25.

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Genomic regions influencing the hyperspectral phenome of deoxynivalenol infected wheat.

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Grain Protein Content Phenotyping in Rice via Hyperspectral Imaging Technology and a Genome-Wide Association Study.

Zheng H, Tang W, Yang T, Zhou M, Guo C, Cheng T Plant Phenomics. 2024; 6:0200.

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